charted

name	charted
description	Generate SVG or PNG charts from raw numbers or a CSV using charted, a zero-dependency Python chart library. Covers bar, column, line, scatter, bubble, pie, polar_area, radar, area, box, histogram, heatmap, gantt, combo, and sankey, plus multi-series data, named palettes, and a CLI. Use when asked to plot, chart, or visualize data and produce an image file.

charted

charted turns lists of numbers (or a CSV) into a clean SVG chart. The core library has no runtime dependencies. PNG export pulls in cairosvg as an opt-in extra.

Install

pip install 'charted[png]'   # core + PNG export

Use plain pip install charted if you only need SVG.

Generate a chart in Python

from charted import BarChart

chart = BarChart(
    title="Sales by Quarter",
    data=[120, 180, 210, 150],
    labels=["Q1", "Q2", "Q3", "Q4"],
    width=700,
    height=400,
)
chart.save("sales.svg")   # SVG
chart.save("sales.png")   # PNG (needs charted[png])

save() picks the format from the file extension. Every chart class takes the same core arguments: data, labels, title, width, height.

Generate a chart from the CLI

No Python needed. The first CSV column is the x-axis labels, every other column is a data series.

python -m charted create bar output.svg --data sales.csv
python -m charted create bar output.svg --data sales.csv --title "Q3 Sales" --width 900 --height 400
python -m charted batch input_data/ output_svg/

Use --transpose when the CSV is laid out sideways (one series per row, x values across the header row).

Pick a chart type by data shape

Data shape	Use
Values across categories	bar, column
Values over a continuous x	line, area
Two paired numeric variables	scatter (add a size for bubble)
Parts of a whole	pie, polar_area
Several metrics per item	radar
Distribution of one variable	histogram, box
Grid of two categories	heatmap
Tasks over time	gantt
Bars and a line together	combo
Flows between nodes	sankey

All chart types: bar, column, line, scatter, bubble, pie, polar_area, radar, area, box, histogram, heatmap, gantt, combo, sankey.

Import any of them from charted.charts, for example from charted.charts import LineChart, PieChart, ScatterChart.

Multi-series data

Pass a list of lists as data and name each series with series_names. Bar and column charts group side by side by default; set x_stacked=True to stack them.

from charted.charts import ColumnChart

ColumnChart(
    title="Revenue vs Expenses",
    data=[[120, 180, 210], [80, 95, 110]],
    labels=["Q1", "Q2", "Q3"],
    series_names=["Revenue", "Expenses"],
).save("compare.svg")

Themes and palettes

Built-in theme presets: light, dark, high-contrast. Pass one as theme=.

BarChart(data=[120, 180, 210], labels=["Q1", "Q2", "Q3"], theme="dark").save("dark.svg")

Named palettes turn into a list of hex colors via resolve_palette(name), passed as colors=:

from charted import resolve_palette
BarChart(data=[1, 2, 3], colors=resolve_palette("viridis")).save("v.svg")

Named palettes: default, viridis, ocean, categorical, rainbow, monochrome, pastel, sunset, forest, inferno, and the colourblind-safe okabe-ito.

Load a CSV in Python

from charted import load_csv, BarChart

x, y, labels = load_csv("sales.csv", x_col="Quarter", y_col="Revenue")
BarChart(data=y, labels=x, title=labels[0]).save("sales.svg")

load_json works the same way for JSON files.

Show the result

After saving, give the user the file path. SVG opens in any browser and renders inline in Jupyter. PNG is a raster image for slides, docs, or chat. When the user wants an image they can preview, save a .png and hand them that path.

More examples

See examples/ next to this file for short worked scripts: a CSV-to-chart pipeline, a multi-series comparison, and a themed chart.